Abstract
Motivation Carbohydrates play crucial roles in various biochemical processes and are useful for developing drugs and vaccines. However, in case of carbohydrates, the primary structure elucidation is usually a sophisticated task. Therefore, they remain the least structurally characterized class of biomolecules, and it hampers the progress in glycochemistry and glycobiology. Creating a usable instrument designed to assist researchers in natural carbohydrate structure determination would advance glycochemistry in biomedical and pharmaceutical applications. Results We present GRASS (Generation, Ranking and Assignment of Saccharide Structures), a novel method for semi-Automated elucidation of carbohydrate and derivative structures which uses unassigned 13 C NMR spectra and information obtained from chromatography, optical, chemical and other methods. This approach is based on new methods of carbohydrate NMR simulation recently reported as the most accurate. It combines a broad diversity of supported structural features, high accuracy and performance. Availability and implementation GRASS is implemented in a free web tool available at http://csdb.glycoscience.ru/grass.html. Contact [email protected] or [email protected] Supplementary informationSupplementary dataare available at Bioinformatics online.
Original language | English |
---|---|
Pages (from-to) | 957-963 |
Number of pages | 7 |
Journal | Bioinformatics |
Volume | 34 |
Issue number | 6 |
DOIs | |
State | Published - 15 Mar 2018 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© The Author 2017. Published by Oxford University Press. All rights reserved.
Funding
Programming was funded by Russian Science Foundation [grant 14-50-00126]. The underlying study was funded by the Russian Foundation for Basic Research [grant 15-04-01065].
Funders | Funder number |
---|---|
Russian Foundation for Basic Research | 15-04-01065 |
Russian Science Foundation | 14-50-00126 |